System and method of improving communication in a speech communication system

ABSTRACT

A speech communication system and a method of improving communication in such a speech communication system between at least a first user and a second user may be configured so the system (a) transcribes a recorded portion of a speech communication between the at least first and second user to form a transcribed portion, (b) selects and marks at least one of the words of the transcribed portion which is considered to be a keyword of the speech communication, (c) performs a search for each keyword and produces at least one definition for each keyword, (d) calculates a trustworthiness factor for each keyword, each trustworthiness factor indicating a calculated validity of the respective definition(s), and (e) displays the transcribed portion as well as each of the keywords together with the respective definition and the trustworthiness factor thereof to at least one of the first user and the second user.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 15/919,694, which is a continuation of U.S. patentapplication Ser. No. 15/457,227, which is a continuation of U.S. patentapplication Ser. No. 14/799,689, which is a continuation application ofU.S. patent application Ser. No. 13/912,368, filed on Jun. 7, 2013.

FIELD OF THE INVENTION

The present invention relates to a method of improving communication ina speech communication system between at least one first user and onesecond user. Furthermore, the present invention relates to a speechcommunication system for implementing such a method.

BACKGROUND OF THE INVENTION

Knowledge workers are expected to provide their expertise to manydifferent projects within their company. In many cases this results inthe fact that they are involved in various teams, which may also bevirtual teams. They typically have to attend one teleconference orcollaboration session after the other without really having enough timeto prepare themselves completely for the current project context.

In other instances, the knowledge worker just relaxes between theprevious telephone conference and the next one. Assume she or he isgoing to discuss in a telephone conference the new business opportunityfrom an emerging domain that she/he is not familiar with at all. Due toa lack of time she/he is not well-prepared. Nevertheless, it isimportant for her/him to show competencies during the telephoneconference in order to anticipate their participation in the project.

I have determined that it appears that knowledge workers have not yetenough support by the speech communication system they are using forfacing such problems.

SUMMARY OF THE INVENTION

Consequently, it is an object of the present invention to provide amethod and a speech communication system which provides a better supportfor knowledge workers in situations like the ones discussed above,whereby the communication process may be improved and the efficiency ofthe knowledge worker may be increased. Thus, the knowledge worker shouldreceive a maximum of support from the system with a minimum of personalcognitive effort. The object is in other words to provide all therelevant information and context to the persons involved in such acommunication process.

At present, during an on-going speech communication, knowledge workersmay mainly apply an unstructured procedure for retrieving additionalinformation, such as searching on the internet or in certain informationspaces or in e-mail archives. These data sources may be called datarepositories in a generalizing manner. Consequently, the attention ofthe participants in such a speech communication may get heavilydistracted from the main issue of this speech communication, namely thetopic to be discussed. It is to be emphasized that the term “speechcommunication” is to be intended that it refers to any communicationprocess where speech is a part of this process. Examples of such aspeech communication are audio communications such as a telephone callor teleconference, or a video communication such as a video conference.

This problem is solved with a method of improving communication in aspeech communication system according to claim 1, comprising the stepsthat the system;

a) transcribes a recorded portion of a speech communication between theat least first and second user to form a transcribed portion,

b) selects and marks at least one of the words of the transcribedportion which is considered to be a keyword of the speech communication,

c) performs a search for each keyword and produces at least onedefinition for each keyword,

d) calculates a trustworthiness factor for each keyword, eachtrustworthiness factor indicating a calculated validity of therespective definition(s), and

e) displays the transcribed portion as well as each of the keywordstogether with the respective definition and the trustworthiness factorthereof to at least one of the first user and the second user.

The term “portion of a speech communication” is to be understood suchthat also a complete speech communication may be considered and not onlya part of it, as the use case may be.

According to a further aspect of the present invention, this problem canalso be solved by a speech communication system according to claim 13,comprising the following functional entities:

-   -   a transcription unit for transcribing a recorded portion of a        speech communication between the at least first and second user        to form a transcribed portion,    -   a marking unit for selecting and marking at least one of the        words of the transcribed portion which is considered to be a        keyword of the speech communication,    -   a search unit for performing at least one search for each        keyword and producing at least one definition for each keyword,    -   a trustworthiness unit for calculating a trustworthiness factor        for each keyword, each trustworthiness factor indicating a        calculated validity of the respective definition(s), and    -   a display unit for displaying the transcribed portion as well as        each of the keywords together with the respective definition and        the trustworthiness factor thereof to at least one of the first        user and the second user.

Respective advantageous embodiments of the invention are subject-matterof the dependent claims.

Definitions of terms used with respect to this invention:

Similarity is defined as the semantic similarity, whereby a set of termswithin term lists are evaluated on the likeness of theirmeaning/semantic content.

Ontology as defined for computer and information science formallyrepresents knowledge within a domain. Ontologies provide a sharedvocabulary, which can be used to model a domain with the type of objectsand their properties and relations. Ontology organizes information as aform of knowledge representation about a domain. The Web OntologyLanguage (OWL) as defined by W3C is a family of knowledge representationlanguages for authoring ontologies.

Taxonomy applied to information science is a hierarchical structure ofclassified objects. A taxonomy can be regarded as a special, simplifiedontology for which the relations of objects are hierarchical.

Sentiment Detection (also known as Sentiment Analysis or Opinion Mining)refers to the application of natural language processing, computationallinguistics, and text analytics to identify and extract subjectiveinformation in source materials.

Embodiments of the invention may cover, among other things, thefollowing aspects: While a user is in a telephone conference the usermay activate the disclosed method and system. A window may pop upshowing the real-time transcription of the spoken words. Nouns and termsare automatically detected and marked. With a background applicationstructured and unstructured information from internal and external datasources may be searched and consolidated. If augmenting information canbe provided out of these search results the text gets highlighted. Onmouse-over the augmented information is displayed. Alternatively,high-lighting transcription text by the user activates this functionmanually.

Based on the search results, the grade of trustworthiness (i.e. veracityor validity) of the provided, consolidated information is estimated(i.e. calculated) and displayed applying technologies like semanticsimilarity (or semantic relatedness), whereby the likeness of terms inrespect to their meaning/semantic content is determined, and sentimentis detected.

During a subsequent teleconference and collaboration session out of aseries, augmented transcriptions from the previous sessions may bedisplayed in backward chronological order. While scrolling down, theuser can rapidly remember the project context, her/his intendedcontributions, and facilitate consistent positioning to the ongoingdiscussion. If certain terms and references are from a domain with whichthe user is not familiar with, the user typically doesn't want toconsume the time of the other domain experts. Thanks to this invention,highlighted terms provide you with definitions and context, e.g. onmouse-over. High-lighting may apply automatically, e.g. special termswhich are typically outside the regular dictionary, or selected by othermembers of the collaboration team. Most frequent mentioned terms fromthe previous discussion or session series are presented in anautomatically generated 16 tag-cloud providing a flashlight on theproblem space discussed.

The invention applies structured and unstructured search, and semanticsimilarity, to online transcription of a conference/collaborationsession complemented with a trustworthiness indication to create acontextual communication experience. Furthermore, the disclosedembodiments allow for playback of augmented transcriptions fromconcluded sessions or ongoing series of conferencing/collaborationsessions.

Embodiments of the speech communication system and the correspondingmethod of this invention may comprise the following features.Communication systems comprise audio/video conference units for mediamixing, recording, and streaming of media. The transcripting functiontranscribes the audio component of the media into a textualrepresentation. Typically, the transcript contains errors that can beauto-corrected by applying a spell-checker function using a regulardictionary for the language in use. Remaining errors that could not beresolved will be matched against a domain specific dictionary/glossary.If the error can be resolved, the related information is retrieved andlinked to the transcript. Otherwise, the term will be marked andhigh-lighted by the word spotting functional entity. Spotted words arethen applied to a search at information spaces listed in a trustedinformation space directory. Items in this directory are accompaniedwith a trustworthiness factor related to the information space searchedand the type of search applicable. The directory includes references topredefined information spaces that are applicable for structured orunstructured search, e.g. well-known information source like Wikipedia,or applying semantic search typically for information available inintranet or a data warehouse, or for unstructured search e.g. using anintra-/internet search engine. If there are multiple search resultsdelivered, they have to be applied to a similarity check. Thereby, e.g.by means of available ontologies, related terms can be identified. Foreach most frequent similar hit the similarity factor will be raised. Incase of no search hits for an item that is part of a taxonomy, the“father”, “grandfather”, . . . relation can be searched instead of theterm for which the search failed. If there are search results on termsinferred from taxonomies, this is documented and a reducing taxonomyfactor will be considered. Any search results entitled for display maybe condensed (technology available e.g. for smartphone apps) or strippedsuch that they can be recognized within a moment. The trustworthinessfactor may get deducted by (multiplying with) the similarity factor andby a taxonomy factor. The search results are associated with theindividual determined trustworthiness factor and stored in the communitythread glossary and linked to the session transcript. Based on theupdated community thread glossary the tag cloud is recreated. Dependingon a system-wide policy based on the number of retrievals by thecommunication thread community, the search result is also stored in thedomain glossary. Finally, the user interface is updated.

As a further option, the auto-corrected transcript can be translated aspecified language, e.g. to the standard language defined by thecompany.

As further enhancements, sentiment detection technologies can be appliedto individual search results in order to apply a weight factor for thetrustworthiness factor or value, i.e. the sentiment factors for:negative/ironic context, neutral context, positive context. Proposeddefault values may be 0.1, 0.9, and 1, respectively, for these contexts.

As a further option, search results on structured/unstructured searchare examined in respect to reader's evaluation schemes and its grade maybe used as another weight factor for the trustworthiness factor, i.e.the community evaluation factor: e.g. an evaluation “4 of 5 stars”results in a weight factor of 0.8.

The trustworthiness factor may get further deducted by (multiplyingwith) the sentiment factor and the community evaluation factor.

As a further option, the user can judge the trustworthiness of aselected item, e.g. using a move-over context menu and override thevalue. A significant number of average override-values from thecommunity thread will be considered as an additional weight when theitem is stored in the domain glossary.

As described above, there is an interrelation between the method and thesystem according to the invention. Therefore, it is apparent thatfeatures described in connection with the method may be present or evennecessarily present also in the system, and vice versa, although thismay not be mentioned explicitly.

Other objects, features and advantages of the invention(s) disclosedherein may become apparent from the following description(s) thereof.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will be made in detail to embodiments of the disclosure,non-limiting examples of which may be illustrated in the accompanyingdrawing figures (Figs). The figures are generally in the form ofdiagrams. Some elements in the figures may be exaggerated, others may beomitted, for illustrative clarity. Some figures may be in the form ofdiagrams. Although the invention is generally described in the contextof various exemplary embodiments, it should be understood that it is notintended to limit the invention to these particular embodiments, andindividual features of various embodiments may be combined with oneanother. Any text (legends, notes, reference numerals and the like)appearing on the drawings are incorporated by reference herein.

FIG. 1 is a diagram illustrating an exemplary speech communicationsystem which may be suitable for implementing various embodiments of theinvention.

FIG. 2 is a diagram showing a sequence of steps and events which mayoccur or be present in an exemplary method of improving communication ina speech communication system.

FIG. 3 is a diagram showing in more detail a sequence of steps andevents which may occur or be present in the step of determination of thetrustworthiness factor.

FIG. 4 is a diagram showing a sequence of steps and events which mayoccur or be present in an exemplary method of similarity checking as apart of the determination of the trustworthiness factor.

FIG. 5 is a diagram showing a sequence of steps and events which mayoccur or be present in an exemplary method of sentiment detection whichmay be a part of determination of the trustworthiness factor.

FIG. 6 is a diagram which shows in an exemplary manner some componentsof the speech communication system, including a display, on which atranscript window is shown and on which several keywords together withtheir definition and the corresponding trustworthiness factor are shown.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Various embodiments may be described to illustrate teachings of theinvention, and should be construed as illustrative rather than limiting.It should be understood that it is not intended to limit the inventionto these particular embodiments. It should be understood that someindividual features of various embodiments may be combined in differentways than shown, with one another. There may be more than one inventiondescribed herein.

The embodiments and aspects thereof may be described and illustrated inconjunction with systems, devices and methods which are meant to beexemplary and illustrative, not limiting in scope. Specificconfigurations and details may be set forth in order to provide anunderstanding of the invention(s). However, it should be apparent to oneskilled in the art that the invention(s) may be practiced without someof the specific details being presented herein. Furthermore, somewell-known steps or components may be described only generally, or evenomitted, for the sake of illustrative clarity.

Reference herein to “one embodiment”, “an embodiment”, or similarformulations, may mean that a particular feature, structure, operation,or characteristic described in connection with the embodiment, isincluded in at least one embodiment of the present invention. Thus, theappearances of such phrases or formulations herein are not necessarilyall referring to the same embodiment. Furthermore, various particularfeatures, structures, operations, or characteristics may be combined inany suitable manner in one or more embodiments.

In the following descriptions, some specific details may be set forth inorder to provide an understanding of the invention(s) disclosed herein.It should be apparent to those skilled in the art that theseinvention(s) may be practiced without these specific details. Headings(typically in uppercase letters) may be provided as an aid to thereader, and should not be construed as limiting.

Any dimensions and materials or processes set forth herein should beconsidered to be approximate and exemplary, unless otherwise indicated.

FIG. 1 illustrates an exemplary speech communication system 10 (alsoabbreviated “system 10”) which comprises several functional entities.These entities may be designed as distinct units linked with each otheror with a processing unit such as a central processing unit (“CPU”),interconnected processors, a microprocessor, or other type of processor,or they may be for example tasks carried out by a CPU or other type ofprocessor. Furthermore, it is possible that these entities are a mixtureof these configurations. Item 12 indicates that the speech communicationsystem 10 is related to media conferencing. A media recording unit 14 ispart of the media conferencing 12 and is connected with the speechcommunication system 10. A cloud 16 indicates that the speechcommunication system 10 is connected with intranet and/or internet. Itshould be appreciated that embodiments of the communication system 10may include a computer, a server, a media conference server, a laptopcomputer, or a mobile computer device such as a smart phone or internetappliance or tablet. The system may include hardware elements such as adisplay (e.g. a liquid crystal display, a touch actuatable display, amonitor), non-transitory memory (e.g. a hard drive, flash memory, etc.),and input devices (e.g. a keyboard, touch sensitive display screen,mouse, scanner, reader, etc.) that are communicatively connected to aprocessing unit (e.g. a central processing unit, at least one processor,interconnected processors, etc.).

The speech communication system 10 may comprise a transcripting unit 20,a spell-checker unit 22, a word highlighting or word spotting unit 24, asemantic search unit 26, a similarity checker unit 28, and an internetsearch unit 30. Furthermore, the speech communication system 10 cancomprise a marker unit 32 for manual marking and a marking unit 34 forcommunity marking of certain words. Furthermore, a tag cloud creator 36may be included. A display 50 for displaying session tag clouds and adisplay 60 for displaying session transcripts may be provided as well.Furthermore, the system 10 includes a data storage 82 for a regulardictionary (or several regular dictionaries), a data storage 84 for adomain dictionary (which may also be called a glossary), a data storage86 for one or several communication threads created during the speechcommunication, and a data storage 88 for storing a directory of trustedinformation spaces. The system 10 may as well include a data storage 90for dealing with ontologies and taxonomies. It goes without saying thatin an alternative embodiment at least some of the data storages 82-90 orother entities mentioned before may be located outside the system 10 andlinked or connected with the system 10.

The specific functions of the above-mentioned functional entities andtheir respective connections/connectivities as well as the overallfunction of the speech communication system 10 may be better understoodfrom the explanation of an embodiment of the method of improvingcommunication in a speech communication system 10 as depicted in FIG. 2.

As shown in FIG. 2, in a step S101 a real-time media stream or acorresponding recording is accessed to be processed in a step S102,wherein either real-time recorded speech data or replayed segments ofspeech data are used. In a following step S120 these data aretranscribed in order to create a transcribed portion. In this example,the method is carried out sequentially on respective segments of speechdata. As an alternative, the method may be carried out continuously onspeech data as well. In a step S122 a spell-check of the transcribedportion against a regular dictionary stored in a data storage 82 iscarried out in the spell-checker unit 22. The spell-checked transcribedportion forms a so-called communication thread.

The speech data are generated in this example in a telephone callbetween a first user and a second user. It is clear that the speech datamay also stem from a telephone conference between more than just twousers or that these speech data result from a video conference.

Thereafter, the spell-checker unit 22 carries out a spell-check againsta domain dictionary or domain glossary stored in a data storage 84 whichcontains terms frequently used in a certain domain or community.Thereafter, in a step S124 the selecting unit or word spotting unit 24spots words and terms which may be keywords of the communication thread.

In a step S125, the found glossary items are linked to the respectivekeywords. The steps S122, S123, S124, and S125 may be regarded as acombined step S121.

After performing this combined step S121 for the first time, the methodgives a users the possibility to manually mark in a step S132 words ofthe communication thread by using an input device in the form of amanual marking unit 32 (which typically may be a computer mouse) inorder to indicate that the respective word is regarded as a keyword. Thefact that this possibility is open to the user is indicated by thenumber “1” at the arrow pointing to the manual marking step S132. Afterstep S132, the combined step S121 is carried out once again for themanually marked word or words. After the conclusion of the combined stepS121 for the second time, the display on which the results of the stepscarried out so far are shown is updated in a step S110, as indicated bythe number “2” at the arrow pointing to step S110.

In a step S130, the internet search unit 30 performs a structured and/oran unstructured intranet or internet search in order to be able toproduce at least one definition for each of the keywords. It may happenthat by step S130 just one “correct” definition for a respective keywordis found or produced, respectively, and it may well happen that severaldifferent definitions are generated. In a step S126, the semantic searchunit 26 performs a semantic intranet and/or internet search for refiningor correcting the search results of step 130. In a step 128 performedthereafter, the similarity checker unit 28 selects items found on thebasis of similarity. In a step S129, for the items found, information isretrieved and stripped for unnecessary portions.

In a step S400, the trustworthiness analysis unit 40 determines orcalculates, respectively, a trustworthiness factor (thereafter partlyabbreviated with TWF) which indicates theirreliability/veracity/validity of the definition or definitions generatedso far. Then, in a step S131 the selected items are linked to thespotted words and terms. In a step S133, the glossary containing thecommunication thread is updated, i.e. the “new” keywords are added tothe communication thread glossary (which is stored in the data storage86). In a step S134, the manual markings of the other users not yetconsidered in the description of the invention so far are taken intoaccount. In other words, the result of the marking, selecting anddetermining of the TWF of those other users is also taken into account.In a step S135, the cloud of the session tags shown on the respectivedisplay unit 50 is updated. In a step S137, the domain glossary storedin the data storage 84 is updated. Finally, in a further step S110, thedisplay showing the information produced so far is updated again. Atthis point in time, the method of the invention continues with the nextreal-time capturing segment or with the next real-time replay segment,as the case may be. It is of course also possible to apply thisinvention to segments which are not recorded in real-time. This step maybe called a step S139.

In FIG. 3, details of the trustworthiness factor determining step S400are shown. In a step S402, the trustworthiness factor is set to 100%, or1, respectively. In a step S404, it is checked whether the respectiveitem was found in a dictionary or glossary. If this is the case, therespective trustworthiness factor TWF′ from the domain dictionary isretrieved, and this TWF′ replaces the former TWF. Thereafter, in a stepS490 this TWF is saved (in connection with the respective item from thedictionary/glossary).

In case the step S404 reveals that the respective item was not found ina dictionary/glossary, in a step S414 it is checked whether the itemsstem from trusted information spaces such as e.g. Wikipedia. If this isthe case, in a step S416 the TWF is multiplied with a TWF″ which isassociated with a (weighted) average from the respective informationspaces. Afterwards, in step $500 a similarity check is performed, andthen a sentiment detection is carried out in a step S600. Details withrespect to the steps S500 and S600 may be found in connection with thedescription of the FIGS. 4 and 5, respectively. Finally, in the stepS490 the calculated TWF is saved. In case the step S414 reveals that theitems are not from trusted information spaces, in a step S424 it ischecked whether the items result from a structured or unstructuredsearch. If this is the case, the steps S500 of similarity checking andS600 of sentiment detection are carried out, and in the subsequent stepS490 the respective TWF is saved.

If the step S424 reveals that the items are not from astructured/unstructured search, in a step S426 it is checked whether theitems stem from a semantic search using ontologies. If this is the case,again, the steps S500 of similarity checking and S600 of sentimentdetection are carried out, and finally the TWF is saved in the stepS490.

In case the step S426 reveals that the items are not from a semanticsearch using ontologies, it is checked in a step S428 whether the itemsare from a semantic search using taxonomies. If the answer to this checkis “no”, the respective TWF is saved in the step S490. In case theanswer to this check is “yes”, the similarity checking step S500 iscarried out. Thereafter, in a step S430 the present TWF is multipliedwith a taxonomy factor. In other words, in case there are no search hitsfor an item that is part of a taxonomy, the “father”, “grandfather”,relation can be searched instead of the term for which the searchfailed. If there are search results on terms inferred from taxonomies,this is documented and a reducing taxonomy factor will be applied to theTWF. This taxonomy factor may result in a reduction of the TWF. Thetaxonomy factor represents the “distance” in the hierarchy between twoterms, and it is e.g. for the father 75%, for the grandfather 50%, forthe grand-grandfather 25%, and for the brother 85%. After that, thesentiment detection step S600 is carried out, and the respective TWF issaved in the step S490.

In FIG. 4 the process of similarity checking, which was summarized asone single step S500 in the previous discussion, is explained in detail.In a step S502, the first item found is latched in a buffer. In asubsequent step S504 it is checked, whether there are further similaritems. In case there are further similar items, in a step S506 the nextitem found is latched in a buffer and compared in a step S508 with theprevious item in order to perform a similarity checking. To give anexample, SML (=Semantic Measures Library) and a respective toolkit canbe used to compute semantic similarity between semantic elements/terms.The steps S506 and S508 are carried out for each further item found. Assoon as there are no further items, in a step S510 the item list isreduced to those items with the most frequent similarity. In asubsequent step S512 a similarity factor is calculated which is thenumber of the most frequent similar items divided by the total number ofitems. In a subsequent step S514 the current TWF is multiplied with thesimilarity factor calculated in step S512. In a step S516 this modifiedTWF (which is the most current TWF) is returned.

FIG. 5 explains how the sentiment detection step S600 is carried out,which was summarized as one single step S600 in the discussion above. Ina step S602 a sentiment analysis is performed in order to find outwhether in the definition or definitions found so far for the keywordsany sentiment is included. Examples for the sentiment may be negative orironic, positive, or neutral. In other words, the sentiment detectionreveals whether one of the users has a personal assessment orappreciation of a certain word or term which is manifested in therespective communication thread. In case the sentiment analysis in stepS602 reveals that there is a neutral sentiment, the current TWF ismultiplied with a “neutral” sentiment factor in a step S610.

Afterwards, in a step S650, a check for community evaluation isperformed. If it is found that the community, i.e. other readers, havegiven an evaluation, a community evaluation factor is calculated andmultiplied with the TWF found so far. If for example the community givesa ranking of 80% for a certain definition of a keyword, the communityevaluation factor, which is a weight factor, would result in a number of0.8. This calculation and multiplication is carried out in a step S652.Afterwards, the modified TWF is returned in a step S660. In case nocommunity evaluation can be found, the modified TWF is returned“directly” without any multiplication with a community evaluation factorin step S660.

In case the sentiment analysis in step S602 reveals that there is apositive sentiment, the current TWF is multiplied with a “positive”sentiment factor in a step S620. Then, the steps S650-S660 are carriedout. If, however, the sentiment analysis in step S602 reveals that thereis a negative or ironic sentiment, the current TWF is multiplied with a“negative” sentiment factor in a step S630. Then, the steps S650-S660are carried out. In case in the sentiment analysis in step S602 nosentiment at all is found, the steps S650-S660 are carried out withoutany multiplication of the TWF with a sentiment factor.

Just to give an example, the sentiment factor may have a value of 0.1for a negative or an ironic, a value of 0.9 for a neutral, and a valueof 1 for a positive sentiment.

Finally, the respective displays (e.g. user interfaces shown via adisplay unit such as a liquid crystal display or monitor), like the userinterface 70, are updated. That means that a series of updatedinformation is displayed via a display unit. One example for thisdisplay is given in FIG. 6. This view illustrates the way a userexperiences the present speech communication system 10 and thecorresponding method carried out by the system 10. On a transcriptwindow corresponding to a user interface 70, a tag cloud is displayedwhich is schematically and generally referenced with the numeral 51.Three specific tags are shown here as random examples: The tag 52 refersto “big data”, the tag 53 refers to “semantic web”, and the tag 54 isdirected to “augmented reality”. In the respective “stars” in the tags52 to 54, the corresponding trustworthiness factors are displayed. Inother words, the keyword “big data” has a TWF of 95, the keyword“semantic web” has a TWF of 98, and “augmented reality” has a TWF ofonly 85. One portion of the display is a conference control graphicaluser interface which is referenced with the numeral 11. It goes withoutsaying that the display may be updated at any step or at any point intime considered to be useful for the process.

It may well be contemplated to give certain privileges to specifiedusers, e.g. different user rights, in order to allow for overriding thetrustworthiness factor.

While the invention(s) has/have been described with respect to a limitednumber of embodiments, these should not be construed as limitations onthe scope of the invention(s), but rather as examples of some of theembodiments. Those skilled in the art may envision other possiblevariations, modifications, and implementations that are also within thescope of the invention(s), based on the disclosure(s) set forth herein.

What is claimed is:
 1. A method of using a speech communication system,the speech communication system comprising at least one device having atleast one processor communicatively connected to a non-transitorycomputer readable medium, the method comprising: a) transcribing, by thesystem, a recorded portion of a speech communication between at leastone first user and at least one second user to form a transcribedportion, b) identifying, by the system, at least one word of thetranscribed portion identified as a keyword of the speech communication,c) calculating, by the system, a trustworthiness factor for a definitionfor the keyword, the trustworthiness factor indicating a calculatedvalidity of a respective definition for the keyword; and d) displaying,by the system, the transcribed portion so that the definition of thekeyword together with the calculated trustworthiness factor for thedefinition is displayed in response to a pointer being positioned overthe keyword of the displayed transcribed portion or selection of thekeyword of the displayed transcribed portion.
 2. The method of claim 1,wherein each definition is a generated dictionary definition and whereinthe system calculating the trustworthiness factor comprises: the systemperforming: a semantic search using taxonomies in order to generate ataxonomy correction factor for determining the trustworthiness factorfor each definition; a similarity checking which takes into accountsimilarity of different definitions for the keyword in order to generatea similarity correction factor for determining the trustworthinessfactor for each definition; and a sentiment detection which takes intoaccount sentiment with respect to a definition for the keyword togenerate a sentiment correction factor for determining thetrustworthiness factor for that definition; and determining thetrustworthiness factor for each definition based on the taxonomycorrection factor, the similarity correction factor, and the sentimentcorrection factor for the keyword.
 3. The method of claim 1, comprising:performing a spell-check of the transcribed portion using at least oneregular glossary and/or at least one domain glossary.
 4. The method ofclaim 1, wherein: step b) comprises an automatic selecting of keywordsby the system and manually selecting of keywords by a user and/or by acommunity of users using the system.
 5. The method of claim 1,comprising: the system performing a search for the keyword, the searchfor the keyword comprising: the system communicating with at least oneinformation space communicatively connected to the system via at leastone network connection to identify at least one definition for thekeyword for producing a definition for the keyword.
 6. The method ofclaim 5, wherein: step c) comprises the system performing a semanticsearch using ontologies.
 7. The method of claim 5, wherein: the searchfor the keyword also comprises the system performing a semantic searchusing taxonomies in order to generate a taxonomy correction factor formodifying the trustworthiness factor.
 8. The method of claim 1, wherein:step c) comprises the system carrying out similarity checking whichtakes into account similarity of different definitions of the keyword inorder to generate a similarity correction factor for modifying thetrustworthiness factor.
 9. The method of claim 1, wherein: step c)comprises the system carrying out sentiment detection which takes intoaccount the sentiment with respect to at least one definition of thekeyword in order to generate a sentiment correction factor for modifyingthe trustworthiness factor.
 10. The method of claim 1, comprising:positioning speech communication results of the speech communication ina communication thread; and periodically updating a glossary of thecommunication thread.
 11. A non-transitory tangible computer-readablemedium comprising a computer program that defines a method that isperformed by a communication system when a processor of the system runsthe program, the method comprising: a) transcribing, by the system, arecorded portion of a speech communication between at least one firstuser and at least one second user to form a transcribed portion, b)identifying, by the system, at least one word of the transcribed portionidentified as a keyword of the speech communication, c) calculating, bythe system, a trustworthiness factor for a definition for the keyword,the trustworthiness factor indicating a calculated validity of arespective definition for the keyword; and d) displaying, by the system,the transcribed portion so that the definition of the keyword togetherwith the calculated trustworthiness factor for the definition isdisplayed in response to a pointer being positioned over the keyword ofthe displayed transcribed portion or selection of the keyword of thedisplayed transcribed portion.
 12. A speech communication systemcomprising: a non-transitory computer readable medium; a transcriptionunit, the transcription unit configured to transcribe a recorded portionof a speech communication between the at least first and second userstored in the non-transitory computer readable medium to form atranscribed portion, a selecting unit, the selecting unit configured toidentify at least one of the words of the transcribed portion which isconsidered to be a keyword of the speech communication, atrustworthiness unit, the trustworthiness unit configured to calculate atrustworthiness factor for the keyword, each trustworthiness factorindicating a calculated validity of a respective definition for thekeyword; and a display unit, the display unit configured to display thetranscribed portion such that, in response to a pointer being positionedover at least one keyword of the displayed transcribed portion orselection of at least one displayed keyword, displaying of the at leastone definition of the keyword together with the calculatedtrustworthiness factor for each displayed definition is actuated. 13.The speech communication system of claim 12, further comprising: arecording unit, the recording unit configured to record real-time speechcommunication.
 14. The speech communication system of claim 13, furthercomprising: a spell-check unit, the spell-check unit configured to spellcheck the transcribed portion using at least one of a regular domainglossary and a domain glossary.
 15. The speech communication system ofclaim 12, wherein the selection unit is configured to automaticallyselect at least one of the words based on the keyword and the systemfurther comprising: an input device configured such that a manualselecting of the keyword by at least one user is inputtable to thesystem.
 16. The speech communication system of claim 12, comprising: asearch unit, the search unit configured to perform at least one searchfor the keyword to produce at least one definition for the keyword thatidentifies a meaning of the keyword, the search unit is also configuredto search in at least one data repository when performing the at leastone search for the keyword to produce at least one definition for thekeyword.
 17. The speech communication system of claim 12, furthercomprising: a semantic search unit, the semantic search unit configuredto perform a semantic search using ontologies.
 18. The speechcommunication system of claim 12, further comprising: a semantic searchunit, the semantic search unit configured to perform a semantic searchusing taxonomies in order to generate a taxonomy correction factor thatis used to calculate the trustworthiness factor.
 19. The speechcommunication system of claim 18, further comprising: a similarity checkunit, the similarity check unit configured to carry out a similaritychecking step which takes into account the similarity of variousdefinitions of the keyword in order to generate a similarity correctionfactor that is used to calculate the trustworthiness factor.
 20. Thespeech communication system of claim 19, further comprising: a sentimentcheck unit, the sentiment check unit configured to carry out sentimentdetection that takes into account the sentiment with respect to at leastone definition of the keyword in order to generate a sentimentcorrection factor that is used to calculate the trustworthiness factor.